Attributes and Features of Context Relevant to Knowledge Translation in Health Settings: A Response to Recent Commentaries

Background There is growing evidence that context mediates the effects of implementation interventions intended to increase healthcare professionals’ use of research evidence in clinical practice. However, conceptual clarity about what comprises context is elusive. The purpose of this study was to advance conceptual clarity on context by developing the Implementation in Context Framework, a meta-framework of the context domains, attributes and features that can facilitate or hinder healthcare professionals’ use of research evidence and the effectiveness of implementation interventions in clinical practice. Methods We conducted a meta-synthesis of data from three interrelated studies: (1) a concept analysis of published literature on context (n = 70 studies), (2) a secondary analysis of healthcare professional interviews (n = 145) examining context across 11 unique studies and (3) a descriptive qualitative study comprised of interviews with heath system stakeholders (n = 39) in four countries to elicit their tacit knowledge on the attributes and features of context. A rigorous protocol was followed for the meta-synthesis, resulting in development of the Implementation in Context Framework. Following this meta-synthesis, the framework was further refined through feedback from experts in context and implementation science. Results In the Implementation in Context Framework, context is conceptualized in three levels: micro (individual), meso (organizational), and macro (external). The three levels are composed of six contextual domains: (1) actors (micro), (2) organizational climate and structures (meso), (3) organizational social behaviour (meso), (4) organizational response to change (meso), (5) organizational processes (meso) and (6) external influences (macro). These six domains contain 22 core attributes of context and 108 features that illustrate these attributes. Conclusions The Implementation in Context Framework is the only meta-framework of context available to guide implementation efforts of healthcare professionals. It provides a comprehensive and critically needed understanding of the context domains, attributes and features relevant to healthcare professionals’ use of research evidence in clinical practice. The Implementation in Context Framework can inform implementation intervention design and delivery to better interpret the effects of implementation interventions, and pragmatically guide implementation efforts that enhance evidence uptake and sustainability by healthcare professionals.

Section: Discussionmentioning

confidence: 99%

The Implementation in Context (ICON) Framework: A meta-framework of context domains, attributes and features in healthcare

Squires

Graham

Santos

et al. 2023

“…Ensuring research meets the evidence needs of public health policy-makers and practitioners is, therefore, an important strategy to improve its use in decision-making [7][8][9][10]. "Research outcomes" are broad domains or constructs measured to evaluate the impacts of health policies, practices or interventions, such as their effectiveness or acceptability.…”

Section: Introductionmentioning

confidence: 99%

Research outcomes informing the selection of public health interventions and strategies to implement them: A cross-sectional survey of Australian policy-maker and practitioner preferences

Wolfenden,

Hall,

Bauman

et al. 2024

Background A key role of public health policy-makers and practitioners is to ensure beneficial interventions are implemented effectively enough to yield improvements in public health. The use of evidence to guide public health decision-making to achieve this is recommended. However, few studies have examined the relative value, as reported by policy-makers and practitioners, of different broad research outcomes (that is, measures of cost, acceptability, and effectiveness). To guide the conduct of research and better inform public health policy and practice, this study aimed at describing the research outcomes that Australian policy-makers and practitioners consider important for their decision-making when selecting: (a) public health interventions; (b) strategies to support their implementation; and (c) to assess the differences in research outcome preferences between policy-makers and practitioners. Method An online value-weighting survey was conducted with Australian public health policy-makers and practitioners working in the field of non-communicable disease prevention. Participants were presented with a list of research outcomes and were asked to select up to five they considered most critical to their decision-making. They then allocated 100 points across these – allocating more points to outcomes perceived as more important. Outcome lists were derived from a review and consolidation of evaluation and outcome frameworks in the fields of public health knowledge translation and implementation. We used descriptive statistics to report relative preferences overall and for policy-makers and practitioners separately. Results Of the 186 participants; 90 primarily identified as policy-makers and 96 as public health prevention practitioners. Overall, research outcomes of effectiveness, equity, feasibility, and sustainability were identified as the four most important outcomes when considering either interventions or strategies to implement them. Scores were similar for most outcomes between policy-makers and practitioners. Conclusion For Australian policy-makers and practitioners working in the field of non-communicable disease prevention, outcomes related to effectiveness, equity, feasibility, and sustainability appear particularly important to their decisions about the interventions they select and the strategies they employ to implement them. The findings suggest researchers should seek to meet these information needs and prioritize the inclusion of such outcomes in their research and dissemination activities. The extent to which these outcomes are critical to informing the decision of policy-makers and practitioners working in other jurisdictions or contexts warrants further investigation.

“…For example, settings with more formalised leadership and infrastructure (e.g. training, delivery systems, technical resources like those found in schools) may aid intervention implementation and scale-up [ 6 , 17 ], The involvement of end-users across the phases of research is also recommended [ 18 – 20 ]. This improves the compatibility of the intervention to the context or setting where it is to be implemented, and the collection and reporting of information relevant to end-user decision making [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

From trials to communities: implementation and scale-up of health behaviour interventions

McCrabb,

Hall,

McKay

et al. 2023

Background To maximise their potential benefits to communities, effective health behaviour interventions need to be implemented, ideally ‘at scale’, and are often adapted as part of this. To inform future implementation and scale-up efforts, this study broadly sought to understand (i) how often health behaviour interventions are implemented in communities, (ii) the adaptations that occur; (iii) how frequency it occurred ‘at scale’; and (iv) factors associated with ‘scale-up’. Methods A cross-sectional survey was conducted of corresponding authors of trials (randomised or non-randomised) assessing the effects of preventive health behaviour interventions. Included studies of relevant Cochrane reviews served as a sampling frame. Participants were asked to report on the implementation and scale-up (defined as investment in large scale delivery by a (non)government organisation) of their intervention in the community following trial completion, adaptations made, and any research dissemination strategies employed. Information was extracted from published reports of the trial including assessments of effectiveness and risk of bias. Results Authors of 104 trials completed the survey. Almost half of the interventions were implemented following trial completion (taking on average 19 months), and 54% of those were adapted prior to doing so. The most common adaptations were adding intervention components, and adapting the intervention to fit within the local service setting. Scale-up occurred in 33% of all interventions. There were no significant associations between research trial characteristics such as intervention effectiveness, risk of bias, setting, involvement of end-user, and incidence of scale-up. However the number of research dissemination strategies was positively associated to the odds of an intervention being scaled-up (OR = 1.50; 95% CI: 1.19, 1.88; p < 0.001). Conclusions Adaptation of implemented trials is often undertaken. Most health behaviour interventions are not implemented or scaled-up following trial completion. The use of a greater number of dissemination strategies may increase the likelihood of scaled up.